Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Czech
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use maag/whisper_tiny_cs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maag/whisper_tiny_cs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="maag/whisper_tiny_cs")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("maag/whisper_tiny_cs") model = AutoModelForSpeechSeq2Seq.from_pretrained("maag/whisper_tiny_cs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ee72784eb7bb36b231243b3f29bd4480971e3235dfaa71a65be8e4fabf3a842
- Size of remote file:
- 5.63 kB
- SHA256:
- 66a45138f4d6b4c0369115717b0900324e607b752b7546f62616819ae7a11e46
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